4d stereotactic lung imrt planning using monte-carlo dose calculations on multiple rcct-based...
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4D Stereotactic Lung IMRT Planning 4D Stereotactic Lung IMRT Planning using Monte-Carlo Dose Calculations using Monte-Carlo Dose Calculations on Multiple RCCT-based Deformable on Multiple RCCT-based Deformable
GeometriesGeometries
Matthias Söhn1, Di Yan2 and Markus Alber1
(1)University of Tübingen, Radiooncological Clinic, Sect. f. Biomedical Physics, Tübingen, Germany
(2)William Beaumont Hospital, Radiation Oncology,Royal Oak, MI, USA
Forschungszentrum für Hochpräzisionsbetrahlung
2 UKTübingen
SRT for small lesions with large mobility:SRT for small lesions with large mobility:Problems of margin-based, static planningProblems of margin-based, static planning
ITV
PTV
large margins necessary!
dose to large normal tissue volume
restricts tumor dose
what geometry is to be used for dose calculation?
3 UKTübingen
SRT for small lesions with large mobility:SRT for small lesions with large mobility:Problems of margin-based, static planningProblems of margin-based, static planning
static dose distribution,calculated on average CT
…large CTV-motion relative to static planning geometry
…dose distribution changes with CTV-motion
…the actual “dynamic” dose distribution!
static planning
exhaleposition
inhalepositiontumor spends more time in upper part of PTV
region (exhale) than in lower part (inhale)
Is it actually necessary to cover whole PTV region with full dose?
optimize actual dose-to-moving-CTVgated treatment
“Tissue-eye-view”
4 UKTübingen
4D IMRT Planning…4D IMRT Planning…
Our approach in the following:
optimization of the expected dose in moving tissue (Tissue Eye View)
5 UKTübingen
The road to Tissue-Eye-View:The road to Tissue-Eye-View:Dose warping to a reference phaseDose warping to a reference phase
beamlet dose…calc. in different geometries
6 UKTübingen
The road to Tissue-Eye-View:The road to Tissue-Eye-View:Dose warping to a reference phase Dose warping to a reference phase
warped to reference geometry
deformableregistration
beamlet dose…calc. in different geometries
7 UKTübingen
The road to Tissue-Eye-View:The road to Tissue-Eye-View:Probability density function (pdf) of breathingProbability density function (pdf) of breathing
0In
25In
50In
75In
100E
x75
Ex50
Ex25
Ex0
0.1
0.2
0.3
0.4
0.5
time [s]0 50 100
ampl
itude
[a.
u.]
relative time spend in CT-bin=> relative weights
time [s]
am
plit
ud
e
0
100
statistical description of breathing motion!
8 UKTübingen
Tissue-Eye-View: expected dose-to-moving-tissueTissue-Eye-View: expected dose-to-moving-tissue
beamlet dose…calc. in different geometries warped to reference geometry
accumulated inreference geometryusing breathing PDF
TISSUE EYE VIEW
accumulated expected dose distribution in moving tissue, shown in reference geometry
optimizatio
n in tis
sue-eye-view!
optimizatio
n in tis
sue-eye-view!
9 UKTübingen
4D- vs. margin-based static planning: A test case4D- vs. margin-based static planning: A test case
Idealized assumption: perfect daily target-based setup, i.e. no setup-margin
free-breathing PTV-plan: PTV = ITV of all 8 RCCT-phases
free-breathing 4D-plan: optimization of expected dose in ‘tissue-eye-view’ with explicit dose calculation in all 8 RCCT-phases
exhale-gating PTV-plan: PTV = ITV of 3 RCCT-phases around exhale
Comparison of 3 plans…
Implemented using IMRT-software Hyperion:
EUD-based, constrained optimization
Monte-Carlo dose calculation (XVMC)
Prescription: 55Gy EUD to target in 11fx constraints to target (limited overdosage), lung and other unspecified tissue
11 beams
10 UKTübingen
Results: Dose distributions (coronal view)Results: Dose distributions (coronal view)
static dose
accumulated dose accumulated dose
static dose
accumulated dose
57.8Gy 52.2Gy 46.8Gy 38.5Gy 22.0Gy 16.5Gy 11.0Gy27.5Gy
free-breathing PTV-plan exhale-gating PTV-plan free-breathing 4D-plan
lung sparing
11 UKTübingen
Results: Target DVHs (accumulated CTV doses)Results: Target DVHs (accumulated CTV doses)
gating and 4D-plan with similar doses
to moving CTV
free-breathing PTV-plan: lowest and most
inhomogeneous CTV-dose
12 UKTübingen
Results: DVHs of OARs (accumulated doses)Results: DVHs of OARs (accumulated doses)
left (contralateral) lung
skin/unspecified
right (ipsilateral) lung
constraints met similarly well for all plans
13 UKTübingen
Results: EUDs & dosimetric parametersResults: EUDs & dosimetric parameters
objective constraints
EUD
[Gy]
rms overdosage
[Gy]
prescription 55.0 2.0
PTV-plan
-static dose
-accumulated dose
45.1
47.4
1.93.2
gating plan
-static dose
-accumulated dose
49.3
50.9
1.9
2.3
4D-plan
-accumulated dose 50.2 2.0
14 UKTübingen
Results: EUDs & dosimetric parameters, performanceResults: EUDs & dosimetric parameters, performance
objective constraints
calculation time
segmented, fully optimized plan
(Monte Carlo)
EUD
[Gy]
rms overdosage
[Gy]
prescription 55.0 2.0
PTV-plan
-static dose
-accumulated dose
45.1
47.4
1.93.2
60mingating plan
-static dose
-accumulated dose
49.3
50.9
1.9
2.3
4D-plan
-accumulated dose 50.2 2.082min voxel-size: 3mm; beamlet-size: 4x2mm
stat. accuracy MC dose calculation: 3% (3.5•106 histories/segment) dual-quadcore Intel Xeon @ 2.66GHz (8 CPU cores), 16GB memory
15 UKTübingen
Summary & ConclusionsSummary & Conclusions
4D-planning:optimization in Tissue-Eye-View!
explicit dose calculation in multiple geometries using Monte Carlo deformable registration, allowing dose warping to reference geometry optimization of expected dose: dose accumulation in reference geometry using Probability Density Function (pdf) of breathing
potential of dose escalation compared to free-breathing PTV-based planning equal target coverage as gated-treatment, but reduced workload during treatment